Analyze large data sets collected from a long-range IoT system that uses LoRaWAN networking

Use Watson Studio and Python data science packages to identify trends and make predictions

Summary

In this code pattern, we’ll demonstrate how to analyze a large air quality dataset provided by the EPA. This can be considered as a “smart cities” use case. We demonstrate how to analyze large data sets with Watson Studio and Python data science packages. The Jupyter notebook offers a few different examples of how to take advantage of open source software packages to analyze data sets.

As an alternative, we’ll use a dataset that has been generated by the EPA, which measures pollutant levels at several locations throughout the United States. Measurements are taken hourly throughout the year, which enables us to leverage time series analysis.

When you have completed this code pattern, you will understand how to: